TON_IoT_no_scanning / README.md
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---
library_name: transformers
license: mit
base_model: roberta-large
tags:
- generated_from_trainer
model-index:
- name: TON_IoT_no_scanning
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# TON_IoT_no_scanning
This model is a fine-tuned version of [roberta-large](https://huggingface.co/roberta-large) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0000
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 2e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 0.0798 | 1.0 | 750 | 0.0100 |
| 0.0165 | 2.0 | 1500 | 0.0072 |
| 0.0148 | 3.0 | 2250 | 0.0000 |
| 0.0 | 4.0 | 3000 | 0.0000 |
| 0.0 | 5.0 | 3750 | 0.0000 |
### Framework versions
- Transformers 4.45.0.dev0
- Pytorch 2.4.1+cu121
- Datasets 3.0.0
- Tokenizers 0.19.1